AI Engineering Intern (Summer 2027)

AI Engineering Intern – Summer 2027

What Makes Us a Great Place to Work

We are proud to be consistently recognized as one of the world’s best places to work, including being the top-ranked consulting firm on Glassdoor’s Best Places to Work list (earned the #1 spot a record seven times). We bring together a broad set of backgrounds, cultures, experiences, perspectives, and skills in a supportive and inclusive environment where people can thrive professionally and personally.

About Bain AI, Insights & Solutions (AIS)

Bain’s AI, Insights & Solutions (AIS) team works with clients to design and deliver AI-powered solutions that create measurable business impact. You will operate in multidisciplinary teams alongside Bain consultants and other experts in product, design, architecture, and engineering, as well as client stakeholders—translating ambiguous business problems into robust AI applications that can be piloted, scaled, and adopted.

Where You’ll Fit Within the Team

Over the course of a 10-week internship, you will contribute to the design and development of generative AI applications and agentic solutions for Bain’s clients. Working alongside experienced engineers, consultants, and data scientists, you will gain hands-on exposure to the full AI development lifecycle—from early prototyping through production-ready deployment. This is a learning-first role with real project work, mentorship, frequent feedback, and increasing responsibility over time.

Bain offers significant learning and growth opportunities through an apprenticeship model. You will build the technical core of transformations and help move solutions from prototype to real adoption. You will also have opportunities to collaborate with major AI ecosystem partners through Bain’s partnerships, contributing to real client deployments and shaping how emerging capabilities are applied in enterprise settings.

What You’ll Do

• Contribute to the design and development of GenAI applications (e.g., copilots, workflow automation, decision support) using modern LLM stacks
• Support the implementation of AI pipelines and components, including:
  • Retrieval-Augmented Generation (RAG)
  • Fine-tuning and parameter-efficient tuning
  • Embedding generation and optimization
  • Hybrid retrieval strategies (vector, graph, keyword)
• Assist in implementing tool use, function calling, and orchestration across AI workflows
• Assist in building agent capabilities, including context engineering, memory and state management, orchestration, and tool integration
• Support model experimentation, evaluation design, and production deployment tasks alongside senior team members
• Write clean, testable code and contribute to APIs and services through the full SDLC: build, test, deploy, monitor, iterate
• Contribute to evaluation and observability for GenAI systems, including regression test suites, automated scoring, and prompt or policy iteration loops
• Gain exposure to responsible AI practices across system design, including:
  • Implementing guardrails, fallbacks, and human-in-the-loop (HITL) workflows
  • Understanding Bain’s Responsible AI standards and supporting alignment in your work
• Contribute to evaluation harnesses and reusable components that scale across client contexts
• Contribute to ML solutions end-to-end, including:
  • Data preparation, feature engineering, model selection, and training
  • Validation, testing, and performance analysis
  • Applying appropriate ML methods spanning classical ML and deep learning
  • Developing a working knowledge of transformer fundamentals and LLM concepts
• Collaborate with product, engineering, and data science teammates to build well-structured, reliable AI systems
• Communicate clearly in working sessions, demos, and documentation—with both technical and non-technical audiences
• Support client discussions and documentation as part of broader engagement teams

What We’re Looking For

• 0–2+ years of professional AI/ML engineering experience, or equivalent through internships, research, academic projects, or open-source contributions
• Currently pursuing or recently completed a bachelor’s, master’s, or PhD in CS, ML, AI, Data Science, Engineering, or a related quantitative field; or equivalent early-career experience
• Strong academic performance or demonstrated excellence through research, projects, internships, competitions, or open-source contributions
• Proficiency in Python and some experience building APIs or services (e.g., REST/gRPC), or comparable project-based experience
• Experience building complex, multi-stack generative AI programs from conception through production
• Exposure to retrieval and search systems (e.g., vector search, hybrid retrieval, reranking) and familiarity with structured and unstructured data stores
• Exposure to agentic patterns (context management, tool integration, orchestration, memory/state handling); hands-on experience preferred
• Strong engineering practices: testing, code review, version control, CI/CD, and performance profiling
• Excellent interpersonal and communication skills; interest in applying AI to real-world business problems in a client-facing environment

Successful Interns

Successful interns may be considered for full-time offers to begin based on availability and/or graduation date.

Working Mode & Travel

• This role requires in-person collaboration, and you must be based in (or open to working from) New York or San Francisco
• You’ll need to co-locate with your team at least three days a week, whether that’s in a Bain office or at a client site, which may require travel